Crane Hoist Sensor Fusion for Real-Time Danger Assessment
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Solution Overview
Problem
Existing crane operation systems lack effective methods to assess safety and efficiency in real-time, particularly in determining danger levels and optimizing transportation routes, leading to potential accidents and inefficient operations.
Innovation Solution
An information processing apparatus that includes an operation results database to store positional relationships between suspended loads and surrounding obstacles, and a danger level evaluation unit that uses machine learning or statistical methods to assess danger levels and optimize crane operations by determining the best transportation routes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional crane operation methods are used, then the crane can transport suspended loads, but safety cannot be effectively assessed in real-time and accidents may occur
Solution Approach 1:
The patent introduces an information processing apparatus as an intermediary system that includes a database storing positional relationships between suspended loads and surrounding obstacles, and a danger level evaluation unit that processes this data. This intermediary system enables real-time safety assessment without directly modifying the crane's mechanical structure, thus improving reliability while controlling complexity.
Solution Approach 2:
The patent replaces conventional mechanical safety monitoring methods with an information processing system that uses databases and computational evaluation. The danger level evaluation unit substitutes physical safety mechanisms with software-based assessment, reducing mechanical complexity while enhancing safety monitoring capabilities through data analysis.
2Productivity
If conventional route planning is used, then the crane can move between points, but transportation efficiency is not optimized
Solution Approach 1:
The patent implements preliminary action by pre-storing positional relationship data and obstacle information in a database before crane operations begin. The system prepares route optimization data and evaluates danger levels in advance, allowing the crane to efficiently plan transportation routes without real-time computational delays, thus improving productivity.
Solution Approach 2:
The information processing apparatus performs self-service by automatically evaluating danger levels and optimizing routes using stored data without requiring external intervention. The danger level evaluation unit autonomously processes positional relationship data to generate safety assessments and route recommendations, reducing the need for manual planning while improving transportation efficiency.
3Reliability
If basic position monitoring is used, then the crane location can be tracked, but comprehensive safety assessment including danger level determination cannot be performed
Solution Approach 1:
The patent implements feedback by continuously storing positional relationship data between suspended loads and surrounding obstacles in a database, and using this stored information to evaluate danger levels. The system feeds back safety assessment results to operators, enabling comprehensive safety monitoring that utilizes accumulated operational data rather than just real-time position tracking.
Solution Approach 2:
The patent creates copies of operational data by storing positional relationships and obstacle information in a database for later analysis. This copying mechanism allows the system to retain historical operational data and use it for comprehensive safety assessments, preventing loss of valuable information while enhancing safety evaluation capabilities.
4Productivity
If repeated transportation of the same suspended load occurs, then operational patterns emerge, but efficiency improvement opportunities are not identified
Solution Approach 1:
The patent applies preliminary action by pre-storing transportation data for repeated suspended loads in the database, enabling the system to analyze operational patterns before executing subsequent transports. This allows identification of efficiency improvement opportunities in advance, optimizing routes and reducing unnecessary movements based on historical data.
Solution Approach 2:
The information processing apparatus performs self-service by automatically analyzing stored operational data to identify patterns in repeated transportation tasks. The system autonomously detects efficiency improvement opportunities and generates optimized transportation plans without requiring external analysis, thus improving productivity while utilizing retained operational information.
Data Source
AI summary
A camera and a laser radar are attached to the hoist of an overhead crane. Image data and three-dimensional point clouds are acquired during operation and accumulated as operation result data. An information processing apparatus displays the crane's movement trajectory on the terminal and predicts maintenance timing based on operation result data, evaluates a degree of danger and detects an occurrence of accident based on a positional relationship between the crane and an operator, performs optimization of a movement path, a transport sequence of multiple suspended loads, a layout in the facility, and the like, and performs post-operation diagnosis for the degree of danger and operation efficiency of the crane. In addition, the crane is used to scan the inside of the facility to detect abnormalities such as fires and suspicious persons after the work hours of the facility. These treatments can improve the usefulness of the crane.